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537 lines
19 KiB
C++
537 lines
19 KiB
C++
#ifndef OPENCV_MXARRAY_HPP_
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#define OPENCV_MXARRAY_HPP_
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#include <stdint.h>
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#include <string>
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#include <vector>
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#include <opencv2/core.hpp>
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#include "mex.h"
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#include "transpose.hpp"
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/*
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* All recent versions of Matlab ship with the MKL library which contains
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* a blas extension called mkl_?omatcopy(). This defines an out-of-place
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* copy and transpose operation.
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*
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* The mkl library is in ${MATLAB_ROOT}/bin/${MATLAB_MEXEXT}/libmkl...
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* Matlab does not ship headers for the mkl functions, so we define them
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* here.
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*
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* This operation is used extensively to copy between Matlab's column-major
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* format and OpenCV's row-major format.
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*/
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#ifdef __cplusplus
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extern "C" {
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#endif
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#ifdef __cplusplus
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}
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#endif
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/*!
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* @brief raise error if condition fails
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*
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* This is a conditional wrapper for mexErrMsgTxt. If the conditional
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* expression fails, an error is raised and the mex function returns
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* to Matlab, otherwise this function does nothing
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*/
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static void conditionalError(bool expr, const std::string& str) {
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if (!expr) mexErrMsgTxt(std::string("condition failed: ").append(str).c_str());
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}
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/*!
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* @brief raise an error
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*
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* This function is a wrapper around mexErrMsgTxt
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*/
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static void error(const std::string& str) {
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mexErrMsgTxt(str.c_str());
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}
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// ----------------------------------------------------------------------------
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// PREDECLARATIONS
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// ----------------------------------------------------------------------------
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class MxArray;
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template <typename InputScalar, typename OutputScalar>
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void deepCopyAndTranspose(const cv::Mat& src, MxArray& dst);
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template <typename InputScalar, typename OutputScalar>
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void deepCopyAndTranspose(const MxArray& src, cv::Mat& dst);
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// ----------------------------------------------------------------------------
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// MATLAB TRAITS
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// ----------------------------------------------------------------------------
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namespace Matlab {
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class DefaultTraits {};
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class InheritType {};
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static const int Dynamic = -1;
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template<typename _Tp = DefaultTraits> class Traits {
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public:
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static const mxClassID ScalarType = mxUNKNOWN_CLASS;
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static const mxComplexity Complex = mxCOMPLEX;
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static const mxComplexity Real = mxCOMPLEX;
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static std::string ToString() { return "Unknown/Unsupported"; }
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};
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// bool
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template<> class Traits<bool> {
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public:
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static const mxClassID ScalarType = mxLOGICAL_CLASS;
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static std::string ToString() { return "boolean"; }
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};
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// uint8_t
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template<> class Traits<uint8_t> {
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public:
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static const mxClassID ScalarType = mxUINT8_CLASS;
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static std::string ToString() { return "uint8_t"; }
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};
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// int8_t
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template<> class Traits<int8_t> {
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public:
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static const mxClassID ScalarType = mxINT8_CLASS;
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static std::string ToString() { return "int8_t"; }
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};
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// uint16_t
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template<> class Traits<uint16_t> {
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public:
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static const mxClassID ScalarType = mxUINT16_CLASS;
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static std::string ToString() { return "uint16_t"; }
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};
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// int16_t
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template<> class Traits<int16_t> {
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public:
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static const mxClassID ScalarType = mxINT16_CLASS;
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static std::string ToString() { return "int16_t"; }
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};
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// uint32_t
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template<> class Traits<uint32_t> {
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public:
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static const mxClassID ScalarType = mxUINT32_CLASS;
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static std::string ToString() { return "uint32_t"; }
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};
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// int32_t
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template<> class Traits<int32_t> {
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public:
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static const mxClassID ScalarType = mxINT32_CLASS;
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static std::string ToString() { return "int32_t"; }
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};
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// uint64_t
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template<> class Traits<uint64_t> {
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public:
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static const mxClassID ScalarType = mxUINT64_CLASS;
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static std::string ToString() { return "uint64_t"; }
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};
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// int64_t
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template<> class Traits<int64_t> {
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public:
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static const mxClassID ScalarType = mxINT64_CLASS;
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static std::string ToString() { return "int64_t"; }
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};
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// float
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template<> class Traits<float> {
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public:
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static const mxClassID ScalarType = mxSINGLE_CLASS;
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static std::string ToString() { return "float"; }
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};
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// double
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template<> class Traits<double> {
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public:
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static const mxClassID ScalarType = mxDOUBLE_CLASS;
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static std::string ToString() { return "double"; }
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};
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// char
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template<> class Traits<char> {
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public:
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static const mxClassID ScalarType = mxCHAR_CLASS;
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static std::string ToString() { return "char"; }
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};
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// inherited type
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template<> class Traits<Matlab::InheritType> {
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public:
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static std::string ToString() { return "Inherited type"; }
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};
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}
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// ----------------------------------------------------------------------------
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// MXARRAY
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// ----------------------------------------------------------------------------
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/*!
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* @class MxArray
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* @brief A thin wrapper around Matlab's mxArray types
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*
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* MxArray provides a thin object oriented wrapper around Matlab's
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* native mxArray type which exposes most of the functionality of the
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* Matlab interface, but in a more C++ manner. MxArray objects are scoped,
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* so you can freely create and destroy them without worrying about memory
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* management. If you wish to pass the underlying mxArray* representation
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* back to Matlab as an lvalue, see the releaseOwnership() method
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*
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* MxArrays can be directly converted into OpenCV mat objects and std::string
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* objects, since there is a natural mapping between these types. More
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* complex types are mapped through the Bridge which does custom conversions
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* such as MxArray --> cv::Keypoints, etc
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*/
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class MxArray {
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private:
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mxArray* ptr_;
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bool owns_;
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/*!
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* @brief swap all members of this and other
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*
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* the swap method is used by the assignment and move constructors
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* to swap the members of two MxArrays, leaving both in destructible states
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*/
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friend void swap(MxArray& first, MxArray& second) {
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using std::swap;
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swap(first.ptr_, second.ptr_);
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swap(first.owns_, second.owns_);
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}
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void dealloc() {
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if (owns_ && ptr_) { mxDestroyArray(ptr_); ptr_ = NULL; owns_ = false; }
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}
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public:
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// --------------------------------------------------------------------------
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// CONSTRUCTORS
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// --------------------------------------------------------------------------
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/*!
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* @brief default constructor
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*
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* Construct a valid 0x0 matrix (so all other methods do not need validity checks
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*/
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MxArray() : ptr_(mxCreateDoubleMatrix(1, 1, Matlab::Traits<>::Real)), owns_(true) {}
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/*!
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* @brief inheriting constructor
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*
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* Inherit an mxArray from Matlab. Don't claim ownership of the array,
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* just encapsulate it
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*/
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MxArray(const mxArray* ptr) : ptr_(const_cast<mxArray *>(ptr)), owns_(false) {}
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MxArray& operator=(const mxArray* ptr) {
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dealloc();
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ptr_ = const_cast<mxArray *>(ptr);
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owns_ = false;
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return *this;
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}
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/*!
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* @brief explicit typed constructor
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*
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* This constructor explicitly creates an MxArray of the given size and type.
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*/
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MxArray(size_t m, size_t n, size_t k, mxClassID id, mxComplexity com = Matlab::Traits<>::Real) : owns_(true) {
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mwSize dims[] = { static_cast<mwSize>(m), static_cast<mwSize>(n), static_cast<mwSize>(k) };
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ptr_ = mxCreateNumericArray(3, dims, id, com);
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}
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/*!
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* @brief explicit tensor constructor
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*
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* Explicitly construct a tensor of given size and type. Since constructors cannot
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* be explicitly templated, this is a static factory method
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*/
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template <typename Scalar>
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static MxArray Tensor(size_t m, size_t n, size_t k=1) {
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return MxArray(m, n, k, Matlab::Traits<Scalar>::ScalarType);
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}
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/*!
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* @brief explicit matrix constructor
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*
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* Explicitly construct a matrix of given size and type. Since constructors cannot
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* be explicitly templated, this is a static factory method
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*/
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template <typename Scalar>
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static MxArray Matrix(size_t m, size_t n) {
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return MxArray(m, n, 1, Matlab::Traits<Scalar>::ScalarType);
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}
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/*!
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* @brief explicit vector constructor
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*
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* Explicitly construct a vector of given size and type. Since constructors cannot
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* be explicitly templated, this is a static factory method
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*/
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template <typename Scalar>
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static MxArray Vector(size_t m) {
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return MxArray(m, 1, 1, Matlab::Traits<Scalar>::ScalarType);
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}
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/*!
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* @brief explicit scalar constructor
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*
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* Explicitly construct a scalar of given type. Since constructors cannot
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* be explicitly templated, this is a static factory method
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*/
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template <typename Scalar>
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static MxArray Scalar(Scalar value = 0) {
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MxArray s(1, 1, 1, Matlab::Traits<Scalar>::ScalarType);
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s.real<Scalar>()[0] = value;
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return s;
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}
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/*!
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* @brief destructor
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*
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* The destructor deallocates any data allocated by mxCreate* methods only
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* if the object is owned
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*/
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virtual ~MxArray() {
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dealloc();
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}
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/*!
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* @brief copy constructor
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*
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* All copies are deep copies. If you have a C++11 compatible compiler, prefer
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* move construction to copy construction
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*/
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MxArray(const MxArray& other) : ptr_(mxDuplicateArray(other.ptr_)), owns_(true) {}
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/*!
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* @brief copy-and-swap assignment
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*
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* This assignment operator uses the copy and swap idiom to provide a strong
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* exception guarantee when swapping two objects.
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*
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* Note in particular that the other MxArray is passed by value, thus invoking
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* the copy constructor which performs a deep copy of the input. The members of
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* this and other are then swapped
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*/
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MxArray& operator=(MxArray other) {
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swap(*this, other);
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return *this;
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}
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#if __cplusplus >= 201103L
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/*
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* @brief C++11 move constructor
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*
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* When C++11 support is available, move construction is used to move returns
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* out of functions, etc. This is much fast than copy construction, since the
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* move constructed object replaced itself with a default constructed MxArray,
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* which is of size 0 x 0.
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*/
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MxArray(MxArray&& other) : MxArray() {
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swap(*this, other);
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}
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#endif
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/*
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* @brief release ownership to allow return into Matlab workspace
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*
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* MxArray is not directly convertible back to mxArray types through assignment
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* because the MxArray may have been allocated on the free store, making it impossible
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* to know whether the returned pointer will be released by someone else or not.
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*
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* Since Matlab requires mxArrays be passed back into the workspace, the only way
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* to achieve that is through this function, which explicitly releases ownership
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* of the object, assuming the Matlab interpreter receving the object will delete
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* it at a later time
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*
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* e.g.
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* {
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* MxArray A<double>(5, 5); // allocates memory
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* MxArray B<double>(5, 5); // ditto
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* plhs[0] = A; // not allowed!!
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* plhs[0] = A.releaseOwnership(); // makes explicit that ownership is being released
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* } // end of scope. B is released, A isn't
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*
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*/
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mxArray* releaseOwnership() {
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owns_ = false;
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return ptr_;
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}
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template <typename Scalar>
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static MxArray FromMat(const cv::Mat& mat) {
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MxArray arr(mat.rows, mat.cols, mat.channels(), Matlab::Traits<Scalar>::ScalarType);
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switch (mat.depth()) {
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case CV_8U: deepCopyAndTranspose<uint8_t, Scalar>(mat, arr); break;
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case CV_8S: deepCopyAndTranspose<int8_t, Scalar>(mat, arr); break;
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case CV_16U: deepCopyAndTranspose<uint16_t, Scalar>(mat, arr); break;
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case CV_16S: deepCopyAndTranspose<int16_t, Scalar>(mat, arr); break;
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case CV_32S: deepCopyAndTranspose<int32_t, Scalar>(mat, arr); break;
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case CV_32F: deepCopyAndTranspose<float, Scalar>(mat, arr); break;
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case CV_64F: deepCopyAndTranspose<double, Scalar>(mat, arr); break;
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default: error("Attempted to convert from unknown class");
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}
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return arr;
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}
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template <typename Scalar>
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cv::Mat toMat() const {
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cv::Mat mat(rows(), cols(), CV_MAKETYPE(cv::DataType<Scalar>::type, channels()));
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switch (ID()) {
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case mxINT8_CLASS: deepCopyAndTranspose<int8_t, Scalar>(*this, mat); break;
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case mxUINT8_CLASS: deepCopyAndTranspose<uint8_t, Scalar>(*this, mat); break;
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case mxINT16_CLASS: deepCopyAndTranspose<int16_t, Scalar>(*this, mat); break;
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case mxUINT16_CLASS: deepCopyAndTranspose<uint16_t, Scalar>(*this, mat); break;
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case mxINT32_CLASS: deepCopyAndTranspose<int32_t, Scalar>(*this, mat); break;
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case mxUINT32_CLASS: deepCopyAndTranspose<uint32_t, Scalar>(*this, mat); break;
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case mxINT64_CLASS: deepCopyAndTranspose<int64_t, Scalar>(*this, mat); break;
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case mxUINT64_CLASS: deepCopyAndTranspose<uint64_t, Scalar>(*this, mat); break;
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case mxSINGLE_CLASS: deepCopyAndTranspose<float, Scalar>(*this, mat); break;
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case mxDOUBLE_CLASS: deepCopyAndTranspose<double, Scalar>(*this, mat); break;
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case mxCHAR_CLASS: deepCopyAndTranspose<char, Scalar>(*this, mat); break;
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case mxLOGICAL_CLASS: deepCopyAndTranspose<int8_t, Scalar>(*this, mat); break;
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default: error("Attempted to convert from unknown class");
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}
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return mat;
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}
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MxArray field(const std::string& name) { return MxArray(mxGetField(ptr_, 0, name.c_str())); }
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template <typename Scalar>
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Scalar* real() { return static_cast<Scalar *>(mxGetData(ptr_)); }
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template <typename Scalar>
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Scalar* imag() { return static_cast<Scalar *>(mxGetImagData(ptr_)); }
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template <typename Scalar>
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const Scalar* real() const { return static_cast<const Scalar *>(mxGetData(ptr_)); }
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template <typename Scalar>
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const Scalar* imag() const { return static_cast<const Scalar *>(mxGetData(ptr_)); }
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template <typename Scalar>
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Scalar scalar() const { return static_cast<Scalar *>(mxGetData(ptr_))[0]; }
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std::string toString() const {
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conditionalError(isString(), "Attempted to convert non-string type to string");
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std::string str(size()+1, '\0');
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mxGetString(ptr_, const_cast<char *>(str.data()), str.size());
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return str;
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}
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size_t size() const { return mxGetNumberOfElements(ptr_); }
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size_t rows() const { return mxGetDimensions(ptr_)[0]; }
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size_t cols() const { return mxGetDimensions(ptr_)[1]; }
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size_t channels() const { return (mxGetNumberOfDimensions(ptr_) > 2) ? mxGetDimensions(ptr_)[2] : 1; }
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bool isComplex() const { return mxIsComplex(ptr_); }
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bool isNumeric() const { return mxIsNumeric(ptr_); }
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bool isLogical() const { return mxIsLogical(ptr_); }
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bool isString() const { return mxIsChar(ptr_); }
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bool isCell() const { return mxIsCell(ptr_); }
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bool isStructure() const { return mxIsStruct(ptr_); }
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bool isClass(const std::string& name) const { return mxIsClass(ptr_, name.c_str()); }
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std::string className() const { return std::string(mxGetClassName(ptr_)); }
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mxClassID ID() const { return mxGetClassID(ptr_); }
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};
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/*!
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* @brief template specialization for inheriting types
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*
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* This template specialization attempts to preserve the best mapping
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* between OpenCV and Matlab types. Matlab uses double types almost universally, so
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* all floating float types are converted to doubles.
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* Unfortunately OpenCV does not have a native logical type, so
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* that gets mapped to an unsigned 8-bit value
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*/
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template <>
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MxArray MxArray::FromMat<Matlab::InheritType>(const cv::Mat& mat) {
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switch (mat.depth()) {
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case CV_8U: return FromMat<uint8_t>(mat);
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case CV_8S: return FromMat<int8_t>(mat);
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case CV_16U: return FromMat<uint16_t>(mat);
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case CV_16S: return FromMat<int16_t>(mat);
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case CV_32S: return FromMat<int32_t>(mat);
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case CV_32F: return FromMat<double>(mat); //NOTE: Matlab uses double as native type!
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case CV_64F: return FromMat<double>(mat);
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default: error("Attempted to convert from unknown class");
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}
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return MxArray();
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}
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/*!
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* @brief template specialization for inheriting types
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*
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* This template specialization attempts to preserve the best mapping
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* between Matlab and OpenCV types. OpenCV has poor support for double precision
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* types, so all floating point types are cast to float. Logicals get cast
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* to unsignd 8-bit value.
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*/
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template <>
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cv::Mat MxArray::toMat<Matlab::InheritType>() const {
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switch (ID()) {
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case mxINT8_CLASS: return toMat<int8_t>();
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case mxUINT8_CLASS: return toMat<uint8_t>();
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case mxINT16_CLASS: return toMat<int16_t>();
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case mxUINT16_CLASS: return toMat<uint16_t>();
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case mxINT32_CLASS: return toMat<int32_t>();
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case mxUINT32_CLASS: return toMat<int32_t>();
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case mxINT64_CLASS: return toMat<int64_t>();
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case mxUINT64_CLASS: return toMat<int64_t>();
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case mxSINGLE_CLASS: return toMat<float>();
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case mxDOUBLE_CLASS: return toMat<float>(); //NOTE: OpenCV uses float as native type!
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case mxCHAR_CLASS: return toMat<int8_t>();
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case mxLOGICAL_CLASS: return toMat<int8_t>();
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default: error("Attempted to convert from unknown class");
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}
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return cv::Mat();
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}
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|
|
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|
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// ----------------------------------------------------------------------------
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// MATRIX TRANSPOSE
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// ----------------------------------------------------------------------------
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|
|
|
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template <typename InputScalar, typename OutputScalar>
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void deepCopyAndTranspose(const cv::Mat& in, MxArray& out) {
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conditionalError(static_cast<size_t>(in.rows) == out.rows(), "Matrices must have the same number of rows");
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conditionalError(static_cast<size_t>(in.cols) == out.cols(), "Matrices must have the same number of cols");
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conditionalError(static_cast<size_t>(in.channels()) == out.channels(), "Matrices must have the same number of channels");
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|
std::vector<cv::Mat> channels;
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cv::split(in, channels);
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for (size_t c = 0; c < out.channels(); ++c) {
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cv::transpose(channels[c], channels[c]);
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cv::Mat outmat(out.cols(), out.rows(), cv::DataType<OutputScalar>::type,
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static_cast<void *>(out.real<OutputScalar>() + out.cols()*out.rows()*c));
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channels[c].convertTo(outmat, cv::DataType<OutputScalar>::type);
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|
}
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|
|
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//const InputScalar* inp = in.ptr<InputScalar>(0);
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|
//OutputScalar* outp = out.real<OutputScalar>();
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|
//gemt('R', out.rows(), out.cols(), inp, in.step1(), outp, out.rows());
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|
}
|
|
|
|
template <typename InputScalar, typename OutputScalar>
|
|
void deepCopyAndTranspose(const MxArray& in, cv::Mat& out) {
|
|
conditionalError(in.rows() == static_cast<size_t>(out.rows), "Matrices must have the same number of rows");
|
|
conditionalError(in.cols() == static_cast<size_t>(out.cols), "Matrices must have the same number of cols");
|
|
conditionalError(in.channels() == static_cast<size_t>(out.channels()), "Matrices must have the same number of channels");
|
|
std::vector<cv::Mat> channels;
|
|
for (size_t c = 0; c < in.channels(); ++c) {
|
|
cv::Mat outmat;
|
|
cv::Mat inmat(in.cols(), in.rows(), cv::DataType<InputScalar>::type,
|
|
static_cast<void *>(const_cast<InputScalar *>(in.real<InputScalar>() + in.cols()*in.rows()*c)));
|
|
inmat.convertTo(outmat, cv::DataType<OutputScalar>::type);
|
|
cv::transpose(outmat, outmat);
|
|
channels.push_back(outmat);
|
|
}
|
|
cv::merge(channels, out);
|
|
|
|
//const InputScalar* inp = in.real<InputScalar>();
|
|
//OutputScalar* outp = out.ptr<OutputScalar>(0);
|
|
//gemt('C', in.rows(), in.cols(), inp, in.rows(), outp, out.step1());
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|
}
|
|
|
|
|
|
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#endif
|